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Coal will continue to be the main energy source in China for the immediate future, although the environmental pollution and ecological impacts of each stage in the full life cycle of coal mining, transportation, and combustion generate large quantities of external costs. The Late Permian coals in southwestern (SW) China usually contain high amounts of fluorine (F), arsenic (As), and ash, which together with high-F clays cause abnormally high levels of endemic fluorosis, As poisoning, and lung cancer in areas where coal is mined and burned. In this paper, we estimate the external costs of the life cycle of coal. The results show that the externalities of coal in SW China are estimated at USD 73.5 billion or 284.3 USD/t, which would have accounted for 6.5 % of the provincial GDP in this area in 2018. The external cost of human health accounts for 87.2% of the total external costs, of which endemic skeletal fluorosis diseases and related lung cancers have the most important impact. Our study provides a more precise estimate of externalities compared with its counterparts in other provinces in China. Therefore, several policy recommendations would be proposed to internalize the external cost.

The outbreak of SARS-COV-2 disease 2019 (COVID-19) abruptly changed the patterns in electricity consumption, challenging the system operations of forecasting and balancing supply and demand. This is due to the mitigation measures that include lockdown and Work from Home (WFH), which decreased the aggregated demand and remarkably altered its profile. Here, we characterise these changes with various quantitative markers and compare it with pre-COVID-19 business-as-usual data using Great Britain (GB) as a case study. The ripple effects on the generation portfolio, system frequency, forecasting accuracy and imbalance pricing are also analysed. An energy data extraction and pre-processing pipeline that can be used in a variety of similar studies is also presented. Analysis of the GB demand data during the March 2020 lockdown indicates that a shift to WFH will result to a net benefit for flexible stakeholders, such as consumer on variable tariffs. Furthermore, the analysis illustrates a need for faster and more frequent balancing actions, as a result of the increased share of renewable energy in the generation mix. This new equilibrium of energy demand and supply will require a redesign of the existing balancing mechanisms as well as the longer-term power system planning strategies.

Transportation safety, as a critical component of an efficient and reliable transportation system, has been extensively studied with respect to societal economic impacts by transportation agencies and policy officials. However, the embodied energy impact of safety, other than induced congestion, is lacking in studies. This research proposes an energy equivalence of safety (EES) framework to provide a holistic view of the long-term energy and fuel consequences of motor vehicle crashes, incorporating both induced congestion and impacts from lost human productivity resulting from injury and fatal accidents and the energy content resulting from all consequences and activities from a crash. The method utilizes a ratio of gross domestic product (GDP) to national energy consumed in a framework that bridges the gap between safety and energy, leveraging extensive studies of the economic impact of motor vehicle crashes. The energy costs per fatal, injury, and property-damage-only (PDO) crashes in gasoline gallon equivalent (GGE) in 2017 were found to be 200,259, 4442, and 439, respectively, which are significantly greater than impacts from induced congestion alone. The results from the motor vehicle crash data show a decreasing trend of EES per crash type from 2010 and 2017, due primarily in part to a decreasing ratio of total energy consumed to GDP over those years. In addition to the temporal analysis, we conducted a spatial analysis addressing national-, state-, and local-level EES comparisons by using the proposed framework, illustrating its applicability.

This paper presents a systematic and comprehensive mathematical model for alkaline water electrolyzer cells, which can be used for simulation and analysis. The model accounts for factors such as gas evolution reactions, dissolution of gases in the electrolyte, bubble formation, and charge transport. It is based on a numerical two-phase model using the Euler-Euler approach, which has been validated against experimental data for various current densities. The study compares the impact of varying potassium hydroxide (KOH) concentration, separator porosity, and electrolyte flow rates on two-phase flow and bubble coverage. Therefore, the electrolyte in the cell consists of a solution of potassium hydroxide in water. The formation of gas bubbles at the electrodes decreases the electrolyte’s ionic conductivity. Additionally, the presence of these bubbles on the electrode surfaces reduces the available surface area for electrochemical reactions, leading to an increase in the overpotential at a given current density. Furthermore, this paper demonstrates how a neural network and ensembled tree model can predict hydrogen production rates in an alkaline water electrolysis process. The trained neural network accurately predicted the hydrogen production rates, indicating the potential of using neural networks for optimization and control of alkaline water electrolysis processes. The model has an average R-squared value of 0.98, indicating a good fit to the data. A new method of describing bubble transfer, “bubble diffusion,” is introduced to improve performance and reduce costs. The model is solved using COMSOL Multi physics 6.0. The machine learning models in this study were built, trained, and tested using MATLAB software R2020a.

Disposal of municipal solid wastes (MSW) remains a challenge to minimize its impacts on the environment and human health. Landfilling, currently the most common method used for MSW disposal, occupies land space and leads to soil and air emissions. Gasification, an alternative MSW disposal method, can convert waste to energy, but can also lead to soil and air emissions and is a more extensive operation. In this study, life cycle assessments (LCA) of the two disposal methods (landfilling without energy recovery and gasification) were compared to understand impacts on environment and health. The LCA was conducted following the ISO 14040 standards with one ton of MSW as the functional unit. The life cycle inventory was obtained from published journals, technical reports, LandGEM, HELP and GREET database. The impact assessment was done using TRACI 2.1 and categorized into eight groups. The LCA revealed that landfilling is a higher contributor in global warming, acidification, smog formation, eutrophication, ecotoxicity and human health cancer and non-cancer categories. The negative environmental impacts of MSW landfilling can be primarily attributed to the fate of leachate loss and landfill gas, while those of the MSW gasification can be attributed to the disposal of its solid residues.

One of the main retrofitting strategies in warm climates is the reduction of the effects of solar radiation. Cooling loads, and in turn, cooling consumption, can be reduced through the implementation of reflective materials such as solar control films. However, these devices may also negatively affect daylight illuminance conditions and the electric consumption of artificial lighting systems. In a hospital building, it is crucial to meet daylighting requirements as well as indoor illuminance levels and visibility from the inside, as these have a significant impact on health outcomes. The aim of this paper is to evaluate the influence on natural illuminance conditions of a solar control film installed on the windows of a public hospital building in a Mediterranean climate. To this end, a hospital room, with and without solar film, was monitored for a whole year. A descriptive statistical analysis was conducted on the use of artificial lighting, illuminance levels and rolling shutter aperture levels, as well as an analysis of natural illuminance and electric consumption of the artificial lighting system. The addition of a solar control film to the external surface of the window, in combination with the user-controlled rolling shutter aperture levels, has reduced the electric consumption of the artificial lighting system by 12.2%. Likewise, the solar control film has increased the percentage of annual hours with natural illuminance levels by 100–300 lux.

Stress-dominated coal and gas outburst disaster has become one of the main safety problems in deep coal mines. Acoustic emission (AE) or microseismic technology has been viewed as a promising method that can effectively reflect the stress and stability status of rock mass. The AE activity precursor of coal failure is the theoretical basis of this technology. In this study, AE experiments in failure process of coal specimens with different properties and under different stress conditions were performed in laboratory to explore influence factors and their effect of AE activity, and AE activity pattern classification was proposed based on the failure type of coal. The results indicate that the AE activity of different coals under loading are associated with the failure phase, and the evolution pattern of AE activity depends on the failure type of stressed coal. Both the mechanical property and the external stress condition have an important influential effect on the failure type and AE activity pattern in coal failure process. The internal mechanical property decides the inherent tendency of stressed coals to perform brittle or ductile behavior, and the responded AE activity pattern. The contrast of fissure distribution of specimens suggested that fissure structure in coal significantly affects the fracturing mode of coal in uniaxial compression and the AE activity pattern. The external stress condition has a transition effect on AE event energy distribution and AE activity pattern. Under the effect of external stress condition, the energy distribution of AE events was transforming between relative disperse and relative concentration, the failure type and AE activity evolution pattern of coal could appear the brittle-ductile transition. Based on the view of failure type, the pattern of AE activity of coal failure can be classified into three types, i.e., ductile, brittle, and semi-brittle pattern. It is suggested that the high-level AE activity can be viewed as the precursor of brittle instability of coal, and relative quiet phenomenon of AE activity as the precursor of ductile or semi-brittle instability. The research achievement can provide a theoretical base for the prewarning criteria establishment of coal and rock dynamic disasters at depth and improve the insight of AE activity in the coal failure process.

Many factors influence the prices of energy commodities and the value of energy and fuel companies. Among them there are the following factors: economic, social, environmental and political, and recently also the COVID-19 pandemic. The aim of the paper is to examine what the probability and intensity of a decrease in the prices of shares of energy and fuel companies listed on the Warsaw Stock Exchange (Poland) was during the first wave of the pandemic in the first quarter of 2020. The study used the survival analysis methods: the Kaplan-Meier estimator, the test of equality of duration curves and the Cox non-proportional hazards model. The analysis showed that the probability and intensity of price decline of energy and fuel companies in the initial period was the same as that of other companies. The differences become apparent only after 50 days from the established maximum of their value. The risk of price declines in energy and fuel companies increased significantly. This situation was related both to a temporary reduction in demand for energy and fuels, pandemic restrictions introduced in individual countries and the behaviour of stock market investors.